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Introduction of Parallel GPGPU Acceleration Algorithms for the Solution of Radiative TransferGeneral-purpose computing on graphics processing units (GPGPU) is a recent technique that allows the parallel graphics processing unit (GPU) to accelerate calculations performed sequentially by the central processing unit (CPU). To introduce GPGPU to radiative transfer, the Gauss-Seidel solution of the well-known expressions for 1-D and 3-D homogeneous, isotropic media is selected as a test case. Different algorithms are introduced to balance memory and GPU-CPU communication, critical aspects of GPGPU. Results show that speed-ups of one to two orders of magnitude are obtained when compared to sequential solutions. The underlying value of GPGPU is its potential extension in radiative solvers (e.g., Monte Carlo, discrete ordinates) at a minimal learning curve.
Document ID
Document Type
Reprint (Version printed in journal)
Godoy, William F.
(NASA Langley Research Center Hampton, VA, United States)
Liu, Xu
(NASA Langley Research Center Hampton, VA, United States)
Date Acquired
August 25, 2013
Publication Date
January 1, 2011
Publication Information
Publication: Numerical Heat Transfer, Part B: Fundamentals
Volume: 59
Issue: 1
ISSN: 1040-7790
Subject Category
Mathematical And Computer Sciences (General)
Report/Patent Number
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